Geographic Inequities in Healthcare Access Across New York City

Author

Urban Health Insight Group: Matthew, Jason, Zhuohan, Saoni, Imani, Yashvi

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1 Introduction & Motivation

New York City, home to over 8.4 million residents representing immense cultural, ethnic, and socioeconomic diversity, boasts one of the most advanced and extensive healthcare systems globally. World-renowned institutions such as Mount Sinai Health System, NYU Langone Health, and NewYork-Presbyterian/Columbia University Irving Medical Center coexist with a vast network of community health centers, diagnostic and treatment centers, and federally qualified health centers (FQHCs). These facilities provide a broad array of services, from routine primary care to specialized treatments. Despite this infrastructure, achieving equitable access to healthcare remains a persistent and complex challenge, particularly for residents in outer boroughs and historically underserved communities.

Primary care serves as the foundation of effective population health management. It encompasses preventive services like vaccinations and screenings, early intervention for emerging conditions, ongoing management of chronic diseases such as diabetes and hypertension, and coordination of care as the first point of contact for most health concerns. When access to primary care is limited, preventable issues can escalate into emergencies, leading to higher rates of avoidable hospitalizations, increased healthcare costs, and reduced quality of life. Research consistently shows that strong primary care systems correlate with better health outcomes, lower mortality rates, and more efficient resource use across populations.

Citywide metrics, such as the overall number of hospitals or physicians per capita, often paint an overly optimistic picture that masks significant neighborhood-level variations. For the majority of New Yorkers, healthcare access is inherently local, shaped by practical factors including proximity on foot, reliability of public transportation, availability of personal vehicles, and financial constraints. A state-of-the-art hospital in Manhattan might as well be inaccessible to a low-income family in the eastern Bronx reliant on infrequent bus routes or facing childcare barriers during travel.

This project employs a granular, census-tract-level analysis—the smallest geographic unit for which detailed demographic and socioeconomic data are reliably available—to reveal hidden disparities within boroughs and neighborhoods. By examining tracts (approximately 2,000–4,000 residents each across NYC’s roughly 2,300 tracts), we uncover intra-borough inequities and the compounding effects of multiple barriers. We explore how physical distance to facilities intersects with socioeconomic variables, including median household income, health insurance coverage, poverty rates, racial and ethnic composition, and proportions of foreign-born residents.

Recent reports and policy analyses continue to highlight persistent primary care shortages in outer boroughs, alongside gaps in mental health and specialty services. Initiatives such as expansions of school-based health centers in high-need areas of the Bronx and central Brooklyn, increased FQHC funding, and programs like NYC Care (which provides low- or no-cost services to uninsured New Yorkers regardless of immigration status) reflect ongoing efforts to bridge these gaps. As of 2025, workforce shortages, post-pandemic recovery challenges, and uneven facility distribution exacerbate these issues, with studies noting that parts of the Bronx, Queens, and eastern Brooklyn remain underserved despite overall city progress in reducing uninsurance rates.

Understanding these interconnected dynamics has profound policy relevance. Accurate mapping of access deficits allows for precision-targeted interventions: siting new clinics or mobile units, improving transportation linkages, expanding outreach for insurance enrollment, and designing culturally and linguistically appropriate services. True health equity requires not just increasing total resources but directing them strategically to communities with the greatest unmet needs. In 2025, with ongoing reports of primary care provider shortages and borough-level inequalities, this tract-level approach is essential for guiding reforms toward sustainable, inclusive improvements.

2 The Big Question & Why It Matters

Overarching Question (OQ):
How does geographic access to healthcare facilities vary across New York City at the census-tract level, and what socioeconomic disparities exist in healthcare access?

Geographic proximity represents just one dimension of access. Even with a nearby clinic, barriers such as cost, lack of insurance, language differences, cultural mistrust, immigration-related fears, or limited mobility can deter utilization. Affluent residents often mitigate distance through rideshares, taxis, or personal cars, whereas lower-income individuals depend on public transit, which may involve long waits, transfers, or unreliability—especially in outer boroughs. Access, therefore, is multifaceted, influenced by economic, social, and structural factors.

To comprehensively address the overarching question, we decompose it into five interrelated sub-questions, each assigned to a team member for focused analysis:

  1. Geographic Distribution (Matthew): Identifying true “healthcare deserts” as census tracts where less than half the land area falls within a 10-minute walk of any primary care facility.
  2. Borough & Neighborhood Supply (Imani): Quantifying facilities per capita at borough, ZIP code, and tract levels to reveal population-adjusted shortages.
  3. Income & Affordability (Jason): Examining how household income influences timely care utilization, particularly when facilities are physically proximate.
  4. Socioeconomic & Racial Patterns (Zhuohan & Saoni): Assessing correlations between poverty, racial/ethnic composition, foreign-born status, and residence in low-access tracts or uninsurance.
  5. Insurance as a Second Barrier (Yashvi): Investigating how uninsurance rates amplify physical access challenges.

This multidimensional framework moves beyond simplistic proximity metrics to provide a deeper understanding of entrenched inequities and their primary drivers. In a city where outer-borough primary care shortages persist—aligned with recent designations of health professional shortage areas in parts of the Bronx, Brooklyn, and Queens—disentangling these intersections is critical for addressing layered obstacles and promoting equitable outcomes.

3 Data & Approach (Non-Technical)

The analysis draws on two main sources:

  • NYC Facilities Database (from the Department of Health and Mental Hygiene and NYC Open Data portal): Geospatial locations of hospitals, diagnostic/treatment centers, community health centers, FQHCs, and other primary care providers, capturing a comprehensive view of service points.

  • American Community Survey (ACS) tract-level metrics on population, median income, poverty, uninsurance, racial/ethnic breakdowns, foreign-born percentages, and related indicators like language spoken at home.

To measure geographic access, we calculated 10-minute walking isochrones (service areas reachable in approximately 0.5 miles along actual street networks, using network analysis rather than straight-line distances) around each facility. These were overlaid on census tract boundaries to determine the percentage of tract land area covered; tracts with under 50% coverage were classified as deserts. We also computed population-normalized supply rates (facilities per 10,000 residents) at tract, ZIP code, and borough levels, adjusting for density variations.

Statistical relationships were explored through correlation analyses, linear regressions, scatterplots, density plots, and thematic maps. Additional visualizations included choropleth maps for access levels, bar charts for borough comparisons, and bivariate plots for socioeconomic associations. This high-resolution approach unmasks disparities averaged out in borough- or city-level summaries, offering a vivid illustration of overlapping vulnerabilities in an intensely urban setting, where small geographic shifts can reveal stark contrasts in resource availability.

4 Key Findings (Integrated)

Healthcare access in New York City exhibits profound unevenness, shaped by geographic supply deficits, population growth exceeding infrastructure expansion, affordability hurdles, and indirect demographic influences rooted in historical patterns.

Geographic Deserts About 9% of census tracts—encompassing over 500,000 residents—meet the criteria for healthcare deserts, with less than 50% of land area within a 10-minute walk of a facility. These cluster heavily in the Bronx (particularly eastern and southern areas), eastern Brooklyn (including East New York, Brownsville, and Canarsie), and sections of Queens (such as Far Rockaway, Jamaica, and southeastern regions). Manhattan shows near-complete coverage, while western Brooklyn and parts of western Queens perform better. These findings echo longstanding documentation of outer-borough underinvestment in primary care, reinforced by 2024–2025 reports identifying health professional shortage areas in similar neighborhoods.

Figure 1: Healthcare Access Deserts in New York City
Deserts concentrated in outer boroughs, aligning with ongoing disparities.

Population-Adjusted Supply Adjusting for population density sharpens the disparities: Manhattan leads in facilities per 10,000 residents, followed by Brooklyn in raw counts but with many sub-average neighborhoods. Queens and Staten Island lag furthest behind, amid rapid demographic growth in Queens. Recent analyses confirm that primary care facilities remain disproportionately concentrated in Manhattan and parts of Brooklyn, leaving significant gaps in the Bronx and Queens despite citywide efforts and new expansions.

Figure 2: Per-Capita Healthcare Facilities by Borough
Population adjustment exposes outer-borough shortfalls.

Affordability stands out as a critical secondary barrier. Tracts with lower median incomes display higher uninsurance rates, reducing actual utilization even in proximate areas. Citywide uninsurance has improved in recent years through programs like NYC Care and expanded enrollment, but pockets persist in underserved boroughs. Enrollment assistance resources, including NYC Care hubs and community-based navigators, are less dense in Queens, the Bronx, and Staten Island, limiting outreach effectiveness.

Figure 3: Median Household Income and Insurance Coverage
Affordability drives practical access.

Figure 4: Health Insurance Enrollment Centers by Borough
Fewer centers in undeserved boroughs.

The foreign-born population, comprising nearly 40% of New Yorkers in some tracts, shows no strong direct correlation with provider density. Regressions reveal minimal linear relationships, though overlaps occur in immigrant-heavy, low-supply areas. Language barriers, cost concerns, eligibility fears, and cultural factors compound issues for immigrants, even where proximity exists, highlighting the need for multilingual and culturally sensitive services.

Figure 5: Relationship Between Foreign-Born Share and Provider Density
Providers per 10,000 vs. % Foreign-Born: Minimal relationship.

Walking proximity correlates weakly and negatively with income (small effect size, statistically significant but limited practical impact) and shows no meaningful association with racial/ethnic minority share. Low model fit indicates that factors like urban planning, historical investment, transit infrastructure, and policy decisions dominate over direct demographic predictors.

Figure 6: Income vs Healthcare Proximity
Slight negative, small effect.

Figure 7: Minority Share vs Healthcare Proximity
No significant relationship.

Racial/ethnic and immigrant statuses do not strongly predict poor geographic access independently but operate indirectly: marginalized communities disproportionately reside in structurally disadvantaged neighborhoods due to legacies of redlining, segregation, and uneven development. Proximity alone rarely ensures utilization; economic, institutional, and systemic barriers often prevail. Higher-resourced areas better compensate for any distance gaps through alternative means, while vulnerable tracts face compounded deficits. The suite of visualizations—maps highlighting deserts, bars contrasting borough supplies, and scatters illustrating weak direct ties—collectively portrays these nuanced, location-specific inequities in a city striving for equity amid persistent challenges.

5 How This Fits with Prior Research

Our findings resonate with an extensive literature emphasizing distance as a deterrent to preventive care and neighborhood environments as determinants of health outcomes. NYC-specific studies have long documented borough-level gradients in access, exacerbated by pandemics, workforce shortages, and policy shifts. Recent 2024–2025 reports from sources like the Primary Care Development Corporation and state health assessments reaffirm insufficient primary care supply statewide, with urban outer-borough concentrations mirroring our tract-level patterns.

This project’s advancements include updated post-pandemic data, finer tract-resolution revealing subtle deserts overlooked in coarser analyses, and an integrated multidimensional lens. Economic barriers emerge as predominant, with race/ethnicity and nativity exerting indirect effects through structural pathways—consistent with frameworks attributing disparities to systemic inequities rather than individual behaviors. These insights bolster calls for place-based, equity-focused interventions amid persistent challenges like provider shortages and rising demand from aging populations.

6 Limitations & Uncertainty

Several limitations temper the analysis. Facility data lack details on operational capacity, appointment availability, wait times, or service scope and quality, potentially overestimating effective access. Walking-based metrics prioritize pedestrian access but underrepresent transit users, drivers, or those with mobility impairments. The snapshot nature captures correlations, not causation; access may evolve with new openings, closures, or policy changes. Minor data vintage mismatches (e.g., facilities vs. ACS years) introduce slight inconsistencies. Tract-level aggregation smooths intra-tract variations, and cross-tract travel for care is not fully accounted for. Nonetheless, the robust datasets and methods provide a reliable foundation for identifying structural inequities and prioritizing interventions.

7 Implications & Next Steps

Prioritized investments should target confirmed deserts in the Bronx, eastern Brooklyn, and Queens: scaling FQHCs, deploying mobile clinics, enhancing telehealth infrastructure, and establishing new primary care sites. Affordability initiatives require intensified outreach, expanded enrollment navigators (especially in low-density boroughs), and culturally tailored services for immigrant communities.

Broader systemic integration—linking healthcare planning with transportation improvements, affordable housing, and anti-displacement policies—can address mobility and segregation roots. Tackling indirect demographic disparities demands equitable resource allocation and community empowerment.

Future enhancements could incorporate multimodal travel times (bus, subway, bike), real-time utilization data, patient outcome linkages, and longitudinal tracking. Advanced intersectional modeling, including machine learning for predictive access forecasting, would further refine targeted strategies. Ultimately, sustained granular analysis supports evidence-based progress toward health equity in one of the world’s most diverse cities.